Take the pledge to vote

For a better tommorow#AajSawaroApnaKal
  • I agree to receive emails from News18

  • I promise to vote in this year's elections no matter what the odds are.
  • Please check above checkbox.

    SUBMIT

Thank you for
taking the pledge

Vote responsibly as each vote counts
and makes a diffrence

Disclaimer:

Issued in public interest by HDFC Life. HDFC Life Insurance Company Limited (Formerly HDFC Standard Life Insurance Company Limited) (“HDFC Life”). CIN: L65110MH2000PLC128245, IRDAI Reg. No. 101 . The name/letters "HDFC" in the name/logo of the company belongs to Housing Development Finance Corporation Limited ("HDFC Limited") and is used by HDFC Life under an agreement entered into with HDFC Limited. ARN EU/04/19/13618
CO-PRESENTED BY
LIVE TV DownloadNews18 App
News18 English
»
1-min read

Novel Model to Predict Lung Cancer Survival Developed

The findings suggests that the model, using serial image scans of tumours from patients with non-small cell lung cancer (NSCLC), predicted treatment response and survival outcomes better than standard clinical parameters.

Updated:April 22, 2019, 4:01 PM IST
facebookTwittergoogleskypewhatsapp
Novel Model to Predict Lung Cancer Survival Developed
Image for representation. (Photo courtesy: AFP Relaxnews/ anilakkus/ Istock.com)
Researchers have developed a deep-learning model that may help predict lung cancer survival and outcomes.

The findings suggests that the model, using serial image scans of tumours from patients with non-small cell lung cancer (NSCLC), predicted treatment response and survival outcomes better than standard clinical parameters.

"Our research demonstrates that deep-learning models integrating routine imaging scans obtained at multiple time points can improve predictions of survival and cancer-specific outcomes for lung cancer," said Hugo Aerts, Associate Professor at Harvard University.

"By comparison, a standard clinical model relying on stage, gender, age, tumour grade, performance, smoking status, and tumour size could not reliably predict two-year survival or treatment response," Aerts added.

For the study, published in the journal Clinical Cancer Research, the researchers built deep-learning models to see if they could extract more predictive insights as cancers evolve.

They trained their models using serial CT scans of 179 patients with stage 3 NSCLC who had been treated with chemoradiation. They included up to four images per patient obtained routinely before treatment and at one, three, and six months after treatment for a total of 581 images.

The investigators analysed the model's ability to make significant cancer outcome predictions with two datasets -- the training dataset of 581 images and an independent validation dataset of 178 images from 89 patients with non-small cell lung cancer who had been treated with chemoradiation and surgery.

The team found that the models' performance improved with the addition of each follow-up scan. The area under the curve, a measure of the model's accuracy, for predicting two-year survival based on pre-treatment scans alone was 0.58, which improved significantly to 0.74 after adding all available follow-up scans.

Patients classed as having low risk for mortality by the model had six-fold improved overall survival compared with those classed as having high risk.
Read full article
Next Story
Next Story

Also Watch

facebookTwittergoogleskypewhatsapp
 
 

Live TV

Countdown To Elections Results
  • 01 d
  • 12 h
  • 38 m
  • 09 s
To Assembly Elections 2018 Results